Project: Predictive and Proactive Maintenance in Power Systems

Description

This repository contains the analysis of predictive and proactive maintenance in power systems. It includes fault simulation, ML fault prediction, thermographic infrared images analysis from diverse power systems. The aim of the project is to detect failure in the equipment through Computer Vision and Machine Learning methods.

Key Features

• Distribution systems.
• Neural network.
• Fault engine.
• Fault location.

Screenshots

Technologies Used

• [Technology 1]: [Brief description of technology 1 and its role in the project].
• [Technology 2]: [Brief description of technology 2 and its role in the project].
• [Technology 3]: [Brief description of technology 3 and its role in the project].

Contributors

The following individuals have contributed to this project:

• David F. Celeita
• Ana Maria Garzon
• Natalia Laiton
• Victor Sicacha

Institutions

The following institutions are involved in this project:

• Universidad del Rosario

License

Boost Software License 1.0.